2021
Yoann Desmouceaux; Marcel Enguehard; Thomas Clausen
Joint Monitorless Load-Balancing and Autoscaling for Zero-Wait-Time in Data Centers Journal Article
In: IEEE Transactions on Network and Service Management, 18 (1), pp. 672-686, 2021, ISSN: 1932-4537.
Abstract | Links | BibTeX | Tags: Chaire Cisco, Infrastructure for Big Data
@article{Desmouceaux2021,
title = {Joint Monitorless Load-Balancing and Autoscaling for Zero-Wait-Time in Data Centers},
author = {Yoann Desmouceaux and Marcel Enguehard and Thomas Clausen},
url = {https://www.thomasclausen.net/wp-content/uploads/2021/03/Joint-Monitorless-Load-Balancing-and-Autoscaling-for-Zero-Wait-Time-in-Data-Centers.pdf},
doi = {10.1109/TNSM.2020.3045059},
issn = {1932-4537},
year = {2021},
date = {2021-03-01},
journal = {IEEE Transactions on Network and Service Management},
volume = {18},
number = {1},
pages = {672-686},
abstract = {Cloud architectures achieve scaling through two main functions: (i) load-balancers, which dispatch queries among replicated virtualized application instances, and (ii) autoscalers, which automatically adjust the number of replicated instances to accommodate variations in load patterns. These functions are often provided through centralized load monitoring, incurring operational complexity. This article introduces a unified and centralized-monitoring-free architecture achieving both autoscaling and load-balancing, reducing operational overhead while increasing response time performance. Application instances are virtually ordered in a chain, and new queries are forwarded along this chain until an instance, based on its local load, accepts the query. Autoscaling is triggered by the last application instance, which inspects its average load and infers if its chain is under- or over-provisioned. An analytical model of the system is derived, and proves that the proposed technique can achieve asymptotic zero-wait time with high (and controlable) probability. This result is confirmed by extensive simulations, which highlight close-to-ideal performance in terms of both response time and resource costs.},
keywords = {Chaire Cisco, Infrastructure for Big Data},
pubstate = {published},
tppubtype = {article}
}
Cloud architectures achieve scaling through two main functions: (i) load-balancers, which dispatch queries among replicated virtualized application instances, and (ii) autoscalers, which automatically adjust the number of replicated instances to accommodate variations in load patterns. These functions are often provided through centralized load monitoring, incurring operational complexity. This article introduces a unified and centralized-monitoring-free architecture achieving both autoscaling and load-balancing, reducing operational overhead while increasing response time performance. Application instances are virtually ordered in a chain, and new queries are forwarded along this chain until an instance, based on its local load, accepts the query. Autoscaling is triggered by the last application instance, which inspects its average load and infers if its chain is under- or over-provisioned. An analytical model of the system is derived, and proves that the proposed technique can achieve asymptotic zero-wait time with high (and controlable) probability. This result is confirmed by extensive simulations, which highlight close-to-ideal performance in terms of both response time and resource costs.
2018
Yoann Desmouceaux; Sonia Toubaline; Thomas Clausen
Flow-Aware Workload Migration in Data Centers Journal Article
In: Springer - Journal of Network and Systems Management (JONS), 2018.
Abstract | Links | BibTeX | Tags: Chaire Cisco, dc-optimization, Infrastructure for Big Data
@article{Desmouceaux2018a,
title = {Flow-Aware Workload Migration in Data Centers},
author = {Yoann Desmouceaux and Sonia Toubaline and Thomas Clausen},
url = {https://link.springer.com/epdf/10.1007/s10922-018-9452-5?author_access_token=qm_40d91CsNLlZ_vZ0tZFPe4RwlQNchNByi7wbcMAY4xSrvbLplDMLQ3AN9vWEoUIxtZAIdnOGAzJH5W3YOrbGteOLvaEXsEE1xFv66lVxTKlL40BAS25fsaLf8w1RJAvY69owHWqhJkTmAZpvdCkQ%3D%3D
http://www.thomasclausen.net/wp-content/uploads/2018/03/jons-2018.pdf},
doi = {10.1007/s10922-018-9452-5},
year = {2018},
date = {2018-03-10},
journal = {Springer - Journal of Network and Systems Management (JONS)},
abstract = {In data centers, subject to workloads with heterogeneous (and sometimes short) lifetimes, workload migration is a way of attaining a more efficient utilization of the underlying physical machines.
To not introduce performance degradation, such workload migration must take into account not only machine resources, and per-task resource requirements, but also application dependencies in terms of network communication.
This articleformat presents a workload migration model capturing all of these constraints.
A linear programming framework is developed allowing accurate representation of per-task resources requirements and inter-task network demands. Using this, a multi-objective problem is formulated to compute a re-allocation of tasks that (i) maximizes the total inter-task throughput, while (ii) minimizing the cost incurred by migration and (iii) allocating the maximum number of new tasks.
A baseline algorithm, solving this multi-objective problem using the $epsilon$-constraint method is proposed, in order to generate the set of Pareto-optimal solutions. As this algorithm is compute-intensive for large topologies, a heuristic, which computes an approximation of the Pareto front, is then developed, and evaluated on different topologies and with different machine load factors. These evaluations show that the heuristic can provide close-to-optimal solutions, while reducing the solving time by one to two order of magnitudes.},
keywords = {Chaire Cisco, dc-optimization, Infrastructure for Big Data},
pubstate = {published},
tppubtype = {article}
}
In data centers, subject to workloads with heterogeneous (and sometimes short) lifetimes, workload migration is a way of attaining a more efficient utilization of the underlying physical machines.
To not introduce performance degradation, such workload migration must take into account not only machine resources, and per-task resource requirements, but also application dependencies in terms of network communication.
This articleformat presents a workload migration model capturing all of these constraints.
A linear programming framework is developed allowing accurate representation of per-task resources requirements and inter-task network demands. Using this, a multi-objective problem is formulated to compute a re-allocation of tasks that (i) maximizes the total inter-task throughput, while (ii) minimizing the cost incurred by migration and (iii) allocating the maximum number of new tasks.
A baseline algorithm, solving this multi-objective problem using the $epsilon$-constraint method is proposed, in order to generate the set of Pareto-optimal solutions. As this algorithm is compute-intensive for large topologies, a heuristic, which computes an approximation of the Pareto front, is then developed, and evaluated on different topologies and with different machine load factors. These evaluations show that the heuristic can provide close-to-optimal solutions, while reducing the solving time by one to two order of magnitudes.
To not introduce performance degradation, such workload migration must take into account not only machine resources, and per-task resource requirements, but also application dependencies in terms of network communication.
This articleformat presents a workload migration model capturing all of these constraints.
A linear programming framework is developed allowing accurate representation of per-task resources requirements and inter-task network demands. Using this, a multi-objective problem is formulated to compute a re-allocation of tasks that (i) maximizes the total inter-task throughput, while (ii) minimizing the cost incurred by migration and (iii) allocating the maximum number of new tasks.
A baseline algorithm, solving this multi-objective problem using the $epsilon$-constraint method is proposed, in order to generate the set of Pareto-optimal solutions. As this algorithm is compute-intensive for large topologies, a heuristic, which computes an approximation of the Pareto front, is then developed, and evaluated on different topologies and with different machine load factors. These evaluations show that the heuristic can provide close-to-optimal solutions, while reducing the solving time by one to two order of magnitudes.
Yoann Desmouceaux; Thomas Clausen; Juan Antonio Cordero; Mark Townsley
Reliable Multicast with B.I.E.R. Journal Article
In: IEEE/KICS Journal of Communications and Networks (JCN), 20 (2), pp. 182-197, 2018.
Abstract | Links | BibTeX | Tags: B.I.E.R., Chaire Cisco, Infrastructure for Big Data, Performance Evaluation, Reliable Content Distribution
@article{Desmouceaux2018b,
title = {Reliable Multicast with B.I.E.R.},
author = {Yoann Desmouceaux and Thomas Clausen and Juan Antonio Cordero and Mark Townsley},
url = {http://www.thomasclausen.net/wp-content/uploads/2018/03/jcn-2018.pdf},
year = {2018},
date = {2018-03-01},
journal = {IEEE/KICS Journal of Communications and Networks (JCN)},
volume = {20},
number = {2},
pages = {182-197},
abstract = {Inter-network multicast protocols, which build and maintain multicast trees, incur both explicit protocol signalling, and maintenance of state in intermediate routers in the network. B.I.E.R. (Bit-Indexed Explicit Replication) is a technique which can provide a multicast service yet removes such complexities: in- termediate routers are unencumbered by group management, and no per-group state is to be maintained.
This paper explores the use of B.I.E.R. as a basis for develop- ing an efficient and reliable multicast mechanism, where redun- dant traffic is avoided, essential traffic is forwarded along shortest paths, and no per-flow state is required in intermediate routers. Evaluated by way of both an analytical model and network sim- ulation both in generic and in real network topologies with vary- ing background traffic loads, the proposed B.I.E.R.-based reliable multicast mechanism exhibits attractive performance attributes: it attains delivery success rates as high as any other reliable multicast service, but with significantly better link utilisation and no per-flow or per-group state in intermediate routers of the network.},
keywords = {B.I.E.R., Chaire Cisco, Infrastructure for Big Data, Performance Evaluation, Reliable Content Distribution},
pubstate = {published},
tppubtype = {article}
}
Inter-network multicast protocols, which build and maintain multicast trees, incur both explicit protocol signalling, and maintenance of state in intermediate routers in the network. B.I.E.R. (Bit-Indexed Explicit Replication) is a technique which can provide a multicast service yet removes such complexities: in- termediate routers are unencumbered by group management, and no per-group state is to be maintained.
This paper explores the use of B.I.E.R. as a basis for develop- ing an efficient and reliable multicast mechanism, where redun- dant traffic is avoided, essential traffic is forwarded along shortest paths, and no per-flow state is required in intermediate routers. Evaluated by way of both an analytical model and network sim- ulation both in generic and in real network topologies with vary- ing background traffic loads, the proposed B.I.E.R.-based reliable multicast mechanism exhibits attractive performance attributes: it attains delivery success rates as high as any other reliable multicast service, but with significantly better link utilisation and no per-flow or per-group state in intermediate routers of the network.
This paper explores the use of B.I.E.R. as a basis for develop- ing an efficient and reliable multicast mechanism, where redun- dant traffic is avoided, essential traffic is forwarded along shortest paths, and no per-flow state is required in intermediate routers. Evaluated by way of both an analytical model and network sim- ulation both in generic and in real network topologies with vary- ing background traffic loads, the proposed B.I.E.R.-based reliable multicast mechanism exhibits attractive performance attributes: it attains delivery success rates as high as any other reliable multicast service, but with significantly better link utilisation and no per-flow or per-group state in intermediate routers of the network.
2016
Aloys Augustin; Jiazi Yi; Thomas Clausen; Mark Townsley
A Study of LoRa: Long Range & Low Power Networks for the Internet of Things Journal Article
In: MDPI Sensors, 16 (9), pp. 1466, 2016, ISSN: 1424-8220, ((5 yr Impact Factor: 2.437)).
Abstract | Links | BibTeX | Tags: Chaire Cisco, IoT, LoRa, Sensor Networks
@article{Augustin2016,
title = {A Study of LoRa: Long Range & Low Power Networks for the Internet of Things},
author = {Aloys Augustin and Jiazi Yi and Thomas Clausen and Mark Townsley},
url = {http://www.thomasclausen.net/2016-a-study-of-lora-long-range-low-power-networks-for-the-internet-of-things/},
doi = {10.3390/s16091466},
issn = {1424-8220},
year = {2016},
date = {2016-09-09},
journal = {MDPI Sensors},
volume = {16},
number = {9},
pages = {1466},
abstract = {LoRa is a long-range, low-power, low-bitrate, wireless telecommunications system, promoted as an infrastructure solution for the Internet of Things: end-devices use LoRa across a single wireless hop to communicate to gateway(s), connected to the Internet and which act as transparent bridges and relay messages between these end-devices and a central network server. This paper provides an overview of LoRa and an in-depth analysis of its functional components. The physical and data link layer performance is evaluated by field tests and simulations. Based on the analysis and evaluations, some possible solutions for performance enhancements are proposed.},
note = {(5 yr Impact Factor: 2.437)},
keywords = {Chaire Cisco, IoT, LoRa, Sensor Networks},
pubstate = {published},
tppubtype = {article}
}
LoRa is a long-range, low-power, low-bitrate, wireless telecommunications system, promoted as an infrastructure solution for the Internet of Things: end-devices use LoRa across a single wireless hop to communicate to gateway(s), connected to the Internet and which act as transparent bridges and relay messages between these end-devices and a central network server. This paper provides an overview of LoRa and an in-depth analysis of its functional components. The physical and data link layer performance is evaluated by field tests and simulations. Based on the analysis and evaluations, some possible solutions for performance enhancements are proposed.